

def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__			):

						if length <= 0 or not isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
												raise ValueError('''Length must be a positive integer.'''			)
						return [n * (2 * n - 1) for n in range(SCREAMING_SNAKE_CASE__			)]


if __name__ == "__main__":
					print(hexagonal_numbers(length=5))
					print(hexagonal_numbers(length=10))
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


lowerCamelCase__  =					{
    '''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Wav2Vec2Config'''],
    '''feature_extraction_wav2vec2''': ['''Wav2Vec2FeatureExtractor'''],
    '''processing_wav2vec2''': ['''Wav2Vec2Processor'''],
    '''tokenization_wav2vec2''': ['''Wav2Vec2CTCTokenizer''', '''Wav2Vec2Tokenizer'''],
}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__  =					[
       '''WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''Wav2Vec2ForAudioFrameClassification''',
       '''Wav2Vec2ForCTC''',
       '''Wav2Vec2ForMaskedLM''',
       '''Wav2Vec2ForPreTraining''',
       '''Wav2Vec2ForSequenceClassification''',
       '''Wav2Vec2ForXVector''',
       '''Wav2Vec2Model''',
       '''Wav2Vec2PreTrainedModel''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__  =					[
       '''TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFWav2Vec2ForCTC''',
       '''TFWav2Vec2Model''',
       '''TFWav2Vec2PreTrainedModel''',
       '''TFWav2Vec2ForSequenceClassification''',
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__  =					[
       '''FlaxWav2Vec2ForCTC''',
       '''FlaxWav2Vec2ForPreTraining''',
       '''FlaxWav2Vec2Model''',
       '''FlaxWav2Vec2PreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_wavaveca import WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, WavaVecaConfig
   from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
   from .processing_wavaveca import WavaVecaProcessor
   from .tokenization_wavaveca import WavaVecaCTCTokenizer, WavaVecaTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_wavaveca import (
          WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
          WavaVecaForAudioFrameClassification,
          WavaVecaForCTC,
          WavaVecaForMaskedLM,
          WavaVecaForPreTraining,
          WavaVecaForSequenceClassification,
          WavaVecaForXVector,
          WavaVecaModel,
          WavaVecaPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_wavaveca import (
          TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFWavaVecaForCTC,
          TFWavaVecaForSequenceClassification,
          TFWavaVecaModel,
          TFWavaVecaPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_wavaveca import (
          FlaxWavaVecaForCTC,
          FlaxWavaVecaForPreTraining,
          FlaxWavaVecaModel,
          FlaxWavaVecaPreTrainedModel,
      )


else:
   import sys

   lowerCamelCase__  =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




